In recent years, in the application of video surveillance or the like, needs for detecting and tracking a mobile object such as a person or a vehicle are increasing. With such increasing needs, many techniques for detecting a mobile object and tracking the detected mobile object have been proposed. A mobile object herein is not limited to an object which continues to move among objects appeared on an image, and also includes an object which “temporarily stops” (also referred to as “rests” or “loiters”). In other words, a mobile object generally means an object appeared on an image except a portion regarded as a background. For example, a person or a vehicle which is a common target to be monitored by video surveillance is moving not all the time, but has a state of resting such as temporarily stopping or parking. For this reason, it is important in applications such as video surveillance that an object can be detected even when the object temporarily stops.
As a method of detecting a mobile object, a background difference method is known (see, for example, Non Patent Literature 1 and Non Patent Literature 2). The background difference method is a method in which an image stored as a background is compared with an image captured by a camera to extract a region having a difference as a mobile object. Here, when the mobile object is detected by using a background difference, an accurate background extraction is required at the time of analysis. This is because, when data at the start of measurement is simply used as a background fixedly, many error detections occur, caused by influence of a change of the background due to an environmental change such as a change of illumination. Accordingly, in order to avoid such problems, usually, a background at the time of analysis is performed by a method such as calculating a mean value for each pixel from images observed within the latest time period. For example, Non Patent Literature 1 discloses a method of applying a background difference method while performing an update of a background successively.
On the other hand, there is also a technique in which only an object which temporarily rests such as a left object or a person who loiters for a predetermined time is extracted (see, for example, Patent Literature 1). Patent Literature 1 discloses a method in which a motion in a scene is analyzed by a plurality of background models having different time spans. In the method, a long-term background model which is analyzed using a long time range and a short-term background model which is analyzed using a short time range are generated. When a mobile object is not detected by the background difference based on the short-term background model and is detected by the background difference based on the long-term background model for a predetermined times, the mobile object is then detected as being a temporarily stationary object.